Ternary volatile random access memory based on heterogeneous graphene-CMOS fabric

Abstract

Graphene is an emerging nano-material that has garnered immense research interest due to its exotic electrical properties. It is believed to be a potential candidate for post-Si nanoelectronics due to high carrier mobility and extreme scalability. Recently, a new graphene nanoribbon crossbar (xGNR) device was proposed which exhibits negative differential resistance (NDR). In this paper, we present an approach to realize multistate memories, enabled by these graphene crossbar devices. We propose a ternary graphene nanoribbon tunneling volatile random access memory (GNTRAM) and implement it using a heterogeneous integration with CMOS transistors and routing. Benchmarking is presented with respect to state-of-theart CMOS SRAM and 3T DRAM designs. Ternary GNTRAM shows up to 1.77x density-per-bit benefit over CMOS SRAMs and 1.42x benefit over 3T DRAM in 16nm technology node. Ternary GNTRAM is also up to 9x more power-efficient per bit against low-power CMOS SRAMs during stand-by, while maintaining comparable performance to high-performance designs. Thus GNTRAM has the potential to realize ultra-dense nanoscale memories exceeding those achievable by mere physical scaling. Further improvements may be possible by using graphene more extensively, as graphene transistors become available in future.

Low-Power Heterogeneous Graphene Nanoribbon-CMOS Multistate Volatile Memory Circuit

“…This could also be used as a ternary memory cell [Khasanvis et al 2012]. However, these circuits still required physical down-sizing of transistors to scale further.…”

“…Our previous work has explored a binary memory circuit using this xGNR device [Khasanvis et al 2011], which could also function as ternary memory [Khasanvis et al 2012] but did not scale further. In this paper, we present a scaling approach that is different from physical scaling, where the number of bits stored in a single cell can be increased.…”

Parameter variation sensing and estimation in nanoscale fabrics

“…These nanoscale computing systems are based on novel nanostructures, such as nanowires [1], [2], carbon nanotubes [3], graphene [4], [5], magneto electric devices [6], [7], [8], etc. Their manufacturing approaches incorporate unconventional (e.g., self-assembly, nano-imprint) and conventional (e.g., deposition, etching, and lithography) process steps.…”